Comput Methods Programs Biomed - Appraisal of adaptive neuro-fuzzy computing technique for estimating anti-obesity properties of a medicinal plant.

Tópicos

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Resumo

This research examines the precision of an adaptive neuro-fuzzy computing technique in estimating the anti-obesity property of a potent medicinal plant in a clinical dietary intervention. Even though a number of mathematical functions such as SPSS analysis have been proposed for modeling the anti-obesity properties estimation in terms of reduction in body mass index (BMI), body fat percentage, and body weight loss, there are still disadvantages of the models like very demanding in terms of calculation time. Since it is a very crucial problem, in this paper a process was constructed which simulates the anti-obesity activities of caraway (Carum carvi) a traditional medicine on obese women with adaptive neuro-fuzzy inference (ANFIS) method. The ANFIS results are compared with the support vector regression (SVR) results using root-mean-square error (RMSE) and coefficient of determination (R(2)). The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the ANFIS approach. The following statistical characteristics are obtained for BMI loss estimation: RMSE=0.032118 and R(2)=0.9964 in ANFIS testing and RMSE=0.47287 and R(2)=0.361 in SVR testing. For fat loss estimation: RMSE=0.23787 and R(2)=0.8599 in ANFIS testing and RMSE=0.32822 and R(2)=0.7814 in SVR testing. For weight loss estimation: RMSE=0.00000035601 and R(2)=1 in ANFIS testing and RMSE=0.17192 and R(2)=0.6607 in SVR testing. Because of that, it can be applied for practical purposes.

Resumo Limpo

research examin precis adapt neurofuzzi comput techniqu estim antiobes properti potent medicin plant clinic dietari intervent even though number mathemat function spss analysi propos model antiobes properti estim term reduct bodi mass index bmi bodi fat percentag bodi weight loss still disadvantag model like demand term calcul time sinc crucial problem paper process construct simul antiobes activ caraway carum carvi tradit medicin obes women adapt neurofuzzi infer anfi method anfi result compar support vector regress svr result use rootmeansquar error rmse coeffici determin r experiment result show improv predict accuraci capabl general can achiev anfi approach follow statist characterist obtain bmi loss estim rmse r anfi test rmse r svr test fat loss estim rmse r anfi test rmse r svr test weight loss estim rmse r anfi test rmse r svr test can appli practic purpos

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